Timothée Lesort

42 papers B 4Journal 31Unranked 6

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Atlas: A Novel Pathology Foundation Model by Mayo Clinic, Charité, and Aignostics. CoRR Maximilian Alber, Stephan Tietz, Jonas Dippel, Timo Milbich, Timothée Lesort, Panos Korfiatis, Moritz Krügener, Beatriz Perez Cancer, Neelay Shah, Alexander Möllers, Philipp Seegerer, Alexandra Carpen-Amarie, Kai Standvoss, Gabriel Dernbach, Edwin D. de Jong, Simon Schallenberg, Andreas Kunft, Helmut Hoffer von Ankershoffen, Gavin Schaeferle, Patrick Duffy, Matt Redlon, Philipp Jurmeister, David Horst, Lukas Ruff, Klaus-Robert Müller, Frederick Klauschen, Andrew P. Norgan
2024	J	`jnl`	Amplifying pathological detection in EEG signaling pathways through cross-dataset transfer learning. Comput. Biol. Medicine Mohammad-Javad Darvishi Bayazi, Mohammad Sajjad Ghaemi, Timothée Lesort, Md Rifat Arefin, Jocelyn Faubert, Irina Rish
2024	—	`conf`	Continual Learning Under Language Shift. TSD (1) Evangelia Gogoulou, Timothée Lesort, Magnus Boman, Joakim Nivre
2024	B	`conf`	Continual Learning of Deep Neural Networks in The Age of Big Data. ESANN Alexander Gepperth, Timothée Lesort
2024	J	`jnl`	Simple and Scalable Strategies to Continually Pre-train Large Language Models. CoRR Adam Ibrahim, Benjamin Thérien, Kshitij Gupta, Mats L. Richter, Quentin Anthony, Timothée Lesort, Eugene Belilovsky, Irina Rish
2024	J	`jnl`	Simple and Scalable Strategies to Continually Pre-train Large Language Models. Trans. Mach. Learn. Res. Adam Ibrahim, Benjamin Thérien, Kshitij Gupta, Mats L. Richter, Quentin Gregory Anthony, Eugene Belilovsky, Timothée Lesort, Irina Rish
2023	J	`jnl`	A Study of Continual Learning Under Language Shift. CoRR Evangelia Gogoulou, Timothée Lesort, Magnus Boman, Joakim Nivre
2023	J	`jnl`	Amplifying Pathological Detection in EEG Signaling Pathways through Cross-Dataset Transfer Learning. CoRR Mohammad-Javad Darvishi Bayazi, Mohammad Sajjad Ghaemi, Timothée Lesort, Md Rifat Arefin, Jocelyn Faubert, Irina Rish
2023	—	`conf`	Challenging Common Assumptions about Catastrophic Forgetting and Knowledge Accumulation. CoLLAs Timothée Lesort, Oleksiy Ostapenko, Pau Rodríguez, Diganta Misra, Md Rifat Arefin, Laurent Charlin, Irina Rish
2023	J	`jnl`	Continual Pre-Training of Large Language Models: How to (re)warm your model? CoRR Kshitij Gupta, Benjamin Thérien, Adam Ibrahim, Mats L. Richter, Quentin Anthony, Eugene Belilovsky, Irina Rish, Timothée Lesort
2023	—	`conf`	Spurious Features in Continual Learning. AAAI Bridge Program Timothée Lesort
2022	J	`jnl`	Beyond Supervised Continual Learning: a Review. CoRR Benedikt Bagus, Alexander Gepperth, Timothée Lesort
2022	J	`jnl`	Continual Feature Selection: Spurious Features in Continual Learning. CoRR Timothée Lesort
2022	—	`conf`	Continual Learning with Foundation Models: An Empirical Study of Latent Replay. CoLLAs Oleksiy Ostapenko, Timothée Lesort, Pau Rodríguez, Md Rifat Arefin, Arthur Douillard, Irina Rish, Laurent Charlin
2022	J	`jnl`	Foundational Models for Continual Learning: An Empirical Study of Latent Replay. CoRR Oleksiy Ostapenko, Timothée Lesort, Pau Rodríguez, Md Rifat Arefin, Arthur Douillard, Irina Rish, Laurent Charlin
2022	J	`jnl`	Scaling the Number of Tasks in Continual Learning. CoRR Timothée Lesort, Oleksiy Ostapenko, Diganta Misra, Md Rifat Arefin, Pau Rodríguez, Laurent Charlin, Irina Rish
2022	B	`conf`	Tutorial - Continual Learning beyond classification. ESANN Alexander Gepperth, Timothée Lesort
2021	J	`jnl`	Continual Learning in Deep Networks: an Analysis of the Last Layer. CoRR Timothée Lesort, Thomas George, Irina Rish
2021	J	`jnl`	Continuum: Simple Management of Complex Continual Learning Scenarios. CoRR Arthur Douillard, Timothée Lesort
2021	J	`jnl`	Sequoia: A Software Framework to Unify Continual Learning Research. CoRR Fabrice Normandin, Florian Golemo, Oleksiy Ostapenko, Pau Rodríguez, Matthew D. Riemer, Julio Hurtado, Khimya Khetarpal, Dominic Zhao, Ryan Lindeborg, Timothée Lesort, Laurent Charlin, Irina Rish, Massimo Caccia
2021	J	`jnl`	Understanding Continual Learning Settings with Data Distribution Drift Analysis. CoRR Timothée Lesort, Massimo Caccia, Irina Rish
2020	—	`—`	Apprentissage continu : S'attaquer à l'oubli foudroyant des réseaux de neurones profonds grâce aux méthodes à rejeu de données. (Continual Learning : Tackling Catastrophic Forgetting in Deep Neural Networks with Replay Processes). Timothée Lesort
2020	J	`jnl`	Continual Learning: Tackling Catastrophic Forgetting in Deep Neural Networks with Replay Processes. CoRR Timothée Lesort
2020	J	`jnl`	Continual learning for robotics: Definition, framework, learning strategies, opportunities and challenges. Inf. Fusion Timothée Lesort, Vincenzo Lomonaco, Andrei Stoian, Davide Maltoni, David Filliat, Natalia Díaz Rodríguez
2019	J	`jnl`	Continual Learning for Robotics. CoRR Timothée Lesort, Vincenzo Lomonaco, Andrei Stoian, Davide Maltoni, David Filliat, Natalia Díaz Rodríguez
2019	J	`jnl`	Continual Reinforcement Learning deployed in Real-life using Policy Distillation and Sim2Real Transfer. CoRR René Traoré, Hugo Caselles-Dupré, Timothée Lesort, Te Sun, Natalia Díaz Rodríguez, David Filliat
2019	J	`jnl`	Decoupling feature extraction from policy learning: assessing benefits of state representation learning in goal based robotics. CoRR Antonin Raffin, Ashley Hill, Kalifou René Traoré, Timothée Lesort, Natalia Díaz Rodríguez, David Filliat
2019	B	`conf`	Deep unsupervised state representation learning with robotic priors: a robustness analysis. IJCNN Timothée Lesort, Mathieu Seurin, Xinrui Li, Natalia Díaz Rodríguez, David Filliat
2019	J	`jnl`	DisCoRL: Continual Reinforcement Learning via Policy Distillation. CoRR René Traoré, Hugo Caselles-Dupré, Timothée Lesort, Te Sun, Guanghang Cai, Natalia Díaz Rodríguez, David Filliat
2019	J	`jnl`	Exploring to learn visual saliency: The RL-IAC approach. Robotics Auton. Syst. Céline Craye, Timothée Lesort, David Filliat, Jean-François Goudou
2019	B	`conf`	Generative Models from the perspective of Continual Learning. IJCNN Timothée Lesort, Hugo Caselles-Dupré, Michaël Garcia Ortiz, Andrei Stoian, David Filliat
2019	—	`conf`	Marginal Replay vs Conditional Replay for Continual Learning. ICANN (2) Timothée Lesort, Alexander Gepperth, Andrei Stoian, David Filliat
2019	J	`jnl`	Regularization Shortcomings for Continual Learning. CoRR Timothée Lesort, Andrei Stoian, David Filliat
2019	—	`conf`	Training Discriminative Models to Evaluate Generative Ones. ICANN (3) Timothée Lesort, Andrei Stoian, Jean-François Goudou, David Filliat
2018	J	`jnl`	Exploring to learn visual saliency: The RL-IAC approach. CoRR Céline Craye, Timothée Lesort, David Filliat, Jean-Francois Goudou
2018	J	`jnl`	Generative Models from the perspective of Continual Learning. CoRR Timothée Lesort, Hugo Caselles-Dupré, Michaël Garcia Ortiz, Andrei Stoian, David Filliat
2018	J	`jnl`	Marginal Replay vs Conditional Replay for Continual Learning. CoRR Timothée Lesort, Alexander Gepperth, Andrei Stoian, David Filliat
2018	J	`jnl`	S-RL Toolbox: Environments, Datasets and Evaluation Metrics for State Representation Learning. CoRR Antonin Raffin, Ashley Hill, René Traoré, Timothée Lesort, Natalia Díaz Rodríguez, David Filliat
2018	J	`jnl`	State Representation Learning for Control: An Overview. CoRR Timothée Lesort, Natalia Díaz Rodríguez, Jean-François Goudou, David Filliat
2018	J	`jnl`	State representation learning for control: An overview. Neural Networks Timothée Lesort, Natalia Díaz Rodríguez, Jean-François Goudou, David Filliat
2018	J	`jnl`	Training Discriminative Models to Evaluate Generative Ones. CoRR Timothée Lesort, Jean-François Goudou, David Filliat
2017	J	`jnl`	Unsupervised state representation learning with robotic priors: a robustness benchmark. CoRR Timothée Lesort, Mathieu Seurin, Xinrui Li, Natalia Díaz Rodríguez, David Filliat